Instructions to use ymgong/DeBerta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ymgong/DeBerta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ymgong/DeBerta")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ymgong/DeBerta") model = AutoModelForSequenceClassification.from_pretrained("ymgong/DeBerta", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:faa4c92534b73cbe5b8dd799757aa86208a52866c8b1bd8f35c8f64714fa8c99
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size 737743888
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